This invention relates generally to systems for image coding, and, more particularly, relates to apparatus and methods for coding images for transmission and retrieval over a limited bandwidth communications channel, to attain maximum data compaction with minimum perceptible error.
In recent years, the video information and entertainment market has rapidly expanded and diversified, with the advent of commercial innovations such as pay-per-view services, videotext, and alternative video communication channels, such as telephone lines. Certain developments in this field, however, have been hindered by the limited bandwidth available in the allocated channel and frequency spectrum.
A number of techniques and systems for coding of images have been proposed or developed, with the object of compressing image information for limited bandwidth transmission, storage or retrieval. Conventional coding systems attempt to limit the data rate and communications channel bandwidth required for image transmission or retrieval by decomposing images into subbands. Subband coding is discussed in Karlsson et al, "Subband Coding of Video for Packet Networks," Optical Engineering, Jul. 1988, pp. 574-586, which sets forth a method for dividing a three-dimensional signal into subsampled frequency bands in temporal, horizontal and vertical dimensions, with further spatial analysis of the subband obtained through low pass first stage filtering.
A number of such systems utilize quadrature mirror filters (QMFs) to divide a given image into subbands. See, for example, Gharavi et al, "Application of Quadrature Mirror Filtering to the Coding of Monochrome and Color Images", IEEE. pp. 2384-2386 (1987).
Moreover, certain image processing techniques provide for coding of the various subbands with different levels of precision, in recognition of the non-uniform sensitivity of the human visual system (HVS) to different spatio-temporal components of a given image. The non-uniform response of the HVS is discussed in Glenn et al, "Reduced Bandwidth Requirements for Compatible High Definition Television Transmission," Proceedings of the 38th Annual Broadcast Engineering Conference, National Association of Broadcasters, pp. 297-305, 1984, herein incorporated by reference, which discloses techniques for transmitting low resolution data at high rates and "detail data" at low rates.
Other coding processes utilize vector quantization of images. Quantization is the assignment of representation values to ranges of input values. A vector quantizer, in particular, maps a set of continuous or discrete vectors into a sequence of codes suitable for communication or storage, to achieve data compression. The sequence of codes forms a "codebook" which can be stored in memory. Vector quantizing systems for image processing are discussed in the following publications, herein incorporated by reference:
Gray, "Vector Quantizers", IEEE ASSP Magazine, pp. 4-29 (1984); PA0 Gersho, "On the Structure of Vector Quantizers", Vol. 28, No. 2 IEEE Transaction on Information Theory, pp. 157-166 (1982); PA0 Ramamurthi et al, "Classified Vector Quantization of Images," Vol. 34, No. 11, IEEE Transactions on Communications, pp. 1105-1115 (1986); PA0 Nasrabadi et al, "Image Coding Using Vector Quantization: A Review," Vol. 36, No. 8, IEEE Transactions on Communications, pp. 957-971 (1988); and PA0 Westerink et al, "Subband Coding of Images Using Vector Quantization", Vol. 36, No. 6, IEEE Transactions on Communications, pp. 713-719 (1988).
The Westerink publication presents a two-dimensional vector quantization subband coding technique in which frequency band decomposition of an image is executed by two-dimensional separable QMFs, which split the image spectrum into 16 equal-rate subbands.
Certain coding systems also employ pyramidal image representations, in an effort to provide data compression. In a pyramid image structure, a full-size image is successively filtered and decomposed to form a reduced representation. Pyramid coding systems are presented in Tran et al, "An Efficient Pyramid Imaging Coding System," 1987, IEEE, pp. 744-747, which proposes a pyramid image coding system, using quadrature mirror filters, to form image pyramids for hierarchical image transmission and retrieval. Image pyramids are also discussed in Adelson et al, "Pyramid Methods in Image Processing," 1984, 29-6 RCA Engineer pp. 33-40.
Conventional coding systems, however, continue to require excessive bandwidth and often produce perceptible error in transmission and reconstruction of images.
It is accordingly an object of the invention to provide methods and apparatus for encoding and decoding images for seleCtive storage, or for transmission and retrieval over a bandwidth limited channel, with maximum data compaction and minimum perceptible error.
Conventional coding systems also require complex decoding methods and expensive decoding apparatus, which significantly limit the commercial practicability of such systems.
It is therefore a further object of the invention to provide image coding and decoding methods and apparatus which permit optimal, inexpensive implementation of the decoding process, to enable wide commercial distribution and utilization of such decoders.
Other general and specific objects of the invention will in part be obvious and will in part appear hereinafter.